CAR-T(CAR-T)细胞疗法在非肿瘤性疾病中的应用
Chimeric antigen receptor T (CAR-T) cell therapy in non-oncological diseases.
CAR-T(CAR-T)细胞在血液系统恶性肿瘤中的应用推动了这种免疫治疗形式的显著进展。
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Statistical operating characteristics of current early phase dose finding designs with toxicity and efficacy in oncology.
Statistical operating characteristics of current early phase dose finding designs with toxicity and efficacy in oncology.
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传统I期肿瘤临床试验剂量探索设计旨在根据单一毒性结局确定研究性细胞毒药物的最大耐受剂量(MTD),并假设剂量-反应关系单调。然而,对于肿瘤免疫疗法和分子靶向疗法等新兴疗法,这一假设未必成立,因此基于毒性的传统剂量探索设计不再适用。为应对这一问题,研究者开发了多种早期剂量探索设计,以确定同时考虑毒性和疗效结局的最佳生物学剂量(OBD)。本文综述当前模型辅助剂量探索设计,包括BOIN-ET、BOIN12、UBI、TEPI-2、PRINTE、STEIN和uTPI,以确定OBD并比较其运行特征。我们开展了广泛模拟研究,并利用一项CAR-T 细胞疗法I期试验进行案例分析,在不同可能剂量-反应关系情境下比较上述设计的性能。模拟结果表明,不同设计的表现会因具体剂量-反应关系和所考察指标而异。根据模拟结果和实践考量,STEIN、PRINTE和BOIN12从不同角度看优于其他设计。
Traditional phase I dose finding cancer clinical trial designs aim to determine the maximum tolerated dose (MTD) of the investigational cytotoxic agent based on a single toxicity outcome, assuming a monotone dose-response relationship.
However, this assumption might not always hold for newly emerging therapies such as immuno-oncology therapies and molecularly targeted therapies, making conventional dose finding trial designs based on toxicity no longer appropriate. To tackle this issue, numerous early-phase dose finding clinical trial designs have been developed to identify the optimal biological dose (OBD), which takes both toxicity and efficacy outcomes into account. In this article, we review the current model-assisted dose finding designs, BOIN-ET, BOIN12, UBI, TEPI-2, PRINTE, STEIN, and uTPI to identify the OBD and compare their operating characteristics.
Extensive simulation studies and a case study using a CAR T-cell therapy phase I trial have been conducted to compare the performance of the aforementioned designs under different possible dose-response relationship scenarios. The simulation results demonstrate that the performance of different designs varies depending on the particular dose-response relationship and the specific metric considered. Based on our simulation results and practical considerations, STEIN, PRINTE, and BOIN12 outperform the other designs from different perspectives.
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